Imaging sensors are an important resource in today’s world. Further, a single sensor cannot provide a complete view of the environment in many applications. Just as humans use all five senses to great advantage, computers use image fusion algorithms to gain similar advantages. The resulting fused image, if suitably obtained from a set of source sensor images, can provide a better view of the true scene than the view provided by any of the individual source images. In particular, image sharpening, feature enhancement, better object detection, and improved classification can result. This book explores both the theoretical and practical aspects of image fusion techniques. The approaches include, but are not limited to, statistical methods, color related techniques, model-based methods, and visual information display strategies. Applications of image fusion techniques are also highlighted in this book. The particular applications discussed include medical diagnosis, surveillance systems, biometric systems, remote sensing, nondestructive evaluation, blurred image restoration, and image quality assessment. Each chapter contains a description of research progress on image fusion and highlights methods for solving practical problems with proposed techniques. Due to the intimate relationship between registration and fusion, registering multisensor images is another topic featured. In particular, an in-depth discussion of multisensor image registration can be found in several chapters. In total, this book consists of 16 chapters. Each of these contributions will now be described in more detail.